The arithmetic coding is known as one of the efficient data compressing methods and is widely used in coding standards, such as JBIG, JPEG2000, H.264/AVC, and High-Efficiency Video Coding (HEVC). In H.264/AVC JVT Test Model (JM) and HEVC Test Model (HM), Context-Based Adaptive Binary Arithmetic Coding (CABAC) is adopted as the entropy coding tool for various syntax elements in the video coding system.
FIG. 1 illustrates an example of CABAC encoder 100 which includes three parts: Binarization 110, Context Modeling 120, and Binary Arithmetic Coding (BAC) 130. In the binarization step, each syntax element is uniquely mapped into a binary string (also called bin or bins in this disclosure). In the context modeling step, a probability model is selected for each bin. The corresponding probability model may depend on previously encoded syntax elements, bin indexes, side information, or any combination of the above. After the binarization and the context model assignment, a bin value along with its associated context model is provided to the binary arithmetic coding engine, i.e., the BAC 130 block in FIG. 1. The bin value can be coded in two coding modes depending on the syntax element and bin indexes, where one is the regular coding mode, and the other is the bypass mode. The bins corresponding to regular coding mode are referred to as regular bins and the bins corresponding to bypass coding mode are referred to as bypass bins in this disclosure. In the regular coding mode, the probability of the Most Probable Symbol (MPS) and the probability of the Least Probable Symbol (LPS) for BAC are derived from the associated context model. In the bypass coding mode, the probability of the MPS and the LPS are equal. In CABAC, the bypass mode is introduced to speed up the encoding process.
The simplicity of the bypass coding mode allows the encoding/decoding of the CABAC to be implemented in parallel architecture and to achieve high throughput. However, the encoding/decoding throughput for the regular coding mode cannot be accelerated efficiently due to the complex derivation process of the probability of MPS and LPS. For hardware-based CABAC, the throughput based on a series of regular bins followed by a series of bypass bins is higher than the throughput associated with interleaved regular bins and bypass bins. Therefore, reordering the binarization of syntax elements to collect the bypass bins together can improve the encoding and decoding throughput. In High-Efficiency Video Coding Test Model Version 4.0 (HM-4.0), the binarization of certain syntax elements, such as mvd_l0, mvd_l1, mvd_lc, and coeff_abs_level_minus3, has collected the bypass bins together.
In HM-4.0, for leaf Transform Units (TU) larger than 4×4, the binarization result of last_significant_coeff_x and last_significant_coeff_y can be classified into two parts, one part is processed according to the regular mode and the other part is processed according to the bypass mode. For a leaf TU with width W, if the value of last_significant_coeff_x or last_significant_coeff_y is smaller than W/2, the codeword is binarized with unary code. An exemplary binarization of last_significant_coeff_x and last_significant_coeff_y for an 8×8 TU is shown in Table 1. These unary codes are coded in a regular mode. If the value of last_significant_coeff_x or last_significant_coeff_y is equal to or larger than W/2, the binarized code word is classified into two parts, as shown in Table 1. The first part consists of W/2 bits of zeros which is coded in the regular mode. The second part is log 2(W/2) bits of fixed-length codeword of the value of last_significant_coeff_x or last_significant_coeff_y minus W/2. These fixed-length codes are coded in bypass mode.
TABLE 1BinarizedUnary codewordFixed-length codewordValuecodewordPart (regular mode)Part (bypass mode)0111010120010013000100014000000000000500000100000160000100000107000011000011
It is desirable to further improve the encoding/decoding throughput of CABAC that incorporates a bypass mode.